Re: sas EM RFM Analysis

Welcome! RFM is at the core of many data mining analyses. SAS has many, many options to help you analyze your data. My recommendation is to create some derived variables grouped at the user level, assuming you are trying to determine what types of customers behave differently. Examples include: # visits, # clicks, duration, last_visit. You could then add other metrics that indicate whether they purchased. You could also create variables to indicate where they clicked, so now you a set of measures for each category.

Depending on what your outcome (dependent variable) is, my advice is to see what your data is trying to tell you. Run a Decision Tree, Regression Model, and maybe a Neural Network in Enterprise Miner. Depending on your data, you may want to inpute missing values and even create bins of your interval variables.

If you have Enterprise Guide or Excel, you can use the Rapid Predictive Modeler add-in and point to your data, and let SAS run several methods to determine the best model.

If you want to get fancy, you could start doing Path analysis to determine who people are browsing to the most profitable sites and even use Association/Market Basket to determine rules to assign people to buckets.

Re: sas EM RFM Analysis

Thanks Jonathan!! Really appreciated!! When I asked the question, I had no idea, this community is not only active but also so helpful. Thanks to all of the people. I hope I will be able to help someone someday as well